We address the problem of learning structure in nonlinear Markov networks with continuous variables. This can be viewed as non-Gaussian multidimensional density estimation exploit...
Nonlinear dimensionality reduction is formulated here as the problem of trying to find a Euclidean feature-space embedding of a set of observations that preserves as closely as p...
This paper presents a method for the self-calibration of non-rigid affine structure to a Euclidean co-ordinate frame from only two views by enforcing constraints derived from the ...
: In this paper we present a novel methodology to recognize the layout structure of handwritten filled table-forms. Recognition methodology includes locating line intersections, co...
Point-based rendering is a compact and efficient means of displaying complex geometry. Our goal is to enable flexible point-based rendering, permitting local image refinement, req...